Feature extraction (FE) is an important step in image retrieval, image processing, data
mining and computer vision. FE is the process of extracting relevant information from raw …

Deep learning is presently an effective research area in machine learning technique and
pattern classification association. This has achieved big success in the areas of application …

Image analysis is a prolific field of research which has been broadly studied in the last
decades, successfully applied to a great number of disciplines. Since the apparition of Big …

Feature extraction is the main core in diagnosis, classification, clustering, recognition, and
detection. Many researchers may by interesting in choosing suitable features that used in …

Feature extraction is an important step in image classification. It allows to represent the
content of images as perfectly as possible. However, in this paper, we present a comparison …

Feature extraction and matching is at the base of many computer vision problems, such as
object recognition or structure from motion. Current methods for assessing the performance …

Robustness to noises, outliers, and corruptions is an important issue in linear dimensionality
reduction. Since the sample-specific corruptions and outliers exist, the class-special …

Pattern analysis often requires a pre-processing stage for extracting or selecting features in
order to help the classification, prediction, or clustering stage discriminate or represent the …

In research of pattern recognition, we always want to achieve the correct classification rate
according to the characteristics required. Feature extraction greatly affects the design and …

Recent image retrieval techniques are focusing on multiple image features for the efficient
image retrieval. It has been an inevitable requirement to fetch the images from a variety of …